Structural Equation Model (SEM) of stroke mortality in Spanish inpatient hospital settings: The role of individual and contextual factors
Área Psicología
Structural equation mode
Predictive mode
Inpatient hospital
Issue Date: 
This is an open access article distributed under the Creative Commons: Atribution License (cc BY)
de la Fuente-Arias, J. (Jesús Enrique); García -Torrecillas, J. (Juan Manuel); Solinas, G. (Giulliana); et al. "Structural Equation Model (SEM) of stroke mortality in Spanish inpatient hospital settings: The role of individual and contextual factors". Frontiers in neurology . 10 (498), 2019, 1 - 12
Introduction: Traditionally, predictive models of in-hospital mortality in ischemic stroke have focused on individual patient variables, to the neglect of in-hospital contextual variables. In addition, frequently used scores are betters predictors of risk of sequelae than mortality, and, to date, the use of structural equations in elaborating such measures has only been anecdotal. Aims: The aim of this paper was to analyze the joint predictive weight of the following: (1) individual factors (age, gender, obesity, and epilepsy) on the mediating factors (arrhythmias, dyslipidemia, hypertension), and ultimately death (exitus); (2) contextual in-hospital factors (year and existence of a stroke unit) on the mediating factors (number of diagnoses, procedures and length of stay, and re-admission), as determinants of death; and (3) certain factors in predicting others. Material and Methods: Retrospective cohort study through observational analysis of all hospital stays of Diagnosis Related Group (DRG) 14, non-lysed ischemic stroke, during the time period 2008¿2012. The sample consisted of a total of 186,245 hospital stays, taken from the Minimum Basic Data Set (MBDS) upon discharge from Spanish hospitals. MANOVAs were carried out to establish the linear effect of certain variables on others. These formed the basis for building the Structural Equation Model (SEM), with the corresponding parameters and restrictive indicators. Results: A consistent model of causal predictive relationships between the postulated variables was obtained. One of the most interesting effects was the predictive value of contextual variables on individual variables, especially the indirect effect of the existence of stroke units on reducing number of procedures, readmission and in-hospital mortality. Conclusion: Contextual variables, and specifically the availability of stroke units, made a positive impact on individual variables that affect prognosis and mortality in ischemic stroke. Moreover, it is feasible to determine this impact through the use of structural equation methodology. We analyze the methodological and clinical implications of this type of study for hospital policies.

Files in This Item:
1.12 MB
Adobe PDF

Statistics and impact
0 citas en
0 citas en

Items in Dadun are protected by copyright, with all rights reserved, unless otherwise indicated.